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Deep neural networks (DNNs) have been widely applied in speech recognition and enhancement. In this paper we present some experiments using deep rectifier neural networks for speech denoising. Rectified linear units (ReLUs) can make a sparse connection between hidden layers. We analyze the usage of regularization coefficient during training to encourage more sparseness. This method further improves...
The ability of correlation integral for automatic seizure detection using scalp EEG data has been re-examined in this paper. To facilitate the detection performance and overcome the shortcoming of correlation integral, nonlinear adaptive denoising and Kalman filter have been adopted for pre-processing and post-processing. The three-stage algorithm has achieved 84.6% sensitivity and 0.087/h false detection...
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